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Gambacorta, Nicola, Ciriaco, Fulvio, Amoroso, Nicola, Altomare, Cosimo Damiano, Bajorath, Jürgen, Nicolotti, Orazio (2023) CIRCE: Web-Based Platform for the Prediction of Cannabinoid Receptor Ligands Using Explainable Machine Learning. Journal of Chemical Information and Modeling, 63 (18) 5916-5926 doi:10.1021/acs.jcim.3c00914

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Reference TypeJournal (article/letter/editorial)
TitleCIRCE: Web-Based Platform for the Prediction of Cannabinoid Receptor Ligands Using Explainable Machine Learning
JournalJournal of Chemical Information and Modeling
AuthorsGambacorta, NicolaAuthor
Ciriaco, FulvioAuthor
Amoroso, NicolaAuthor
Altomare, Cosimo DamianoAuthor
Bajorath, JürgenAuthor
Nicolotti, OrazioAuthor
Year2023 (September 25)Volume63
Issue18
PublisherAmerican Chemical Society (ACS)
DOIdoi:10.1021/acs.jcim.3c00914Search in ResearchGate
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Mindat Ref. ID16876129Long-form Identifiermindat:1:5:16876129:8
GUID0
Full ReferenceGambacorta, Nicola, Ciriaco, Fulvio, Amoroso, Nicola, Altomare, Cosimo Damiano, Bajorath, Jürgen, Nicolotti, Orazio (2023) CIRCE: Web-Based Platform for the Prediction of Cannabinoid Receptor Ligands Using Explainable Machine Learning. Journal of Chemical Information and Modeling, 63 (18) 5916-5926 doi:10.1021/acs.jcim.3c00914
Plain TextGambacorta, Nicola, Ciriaco, Fulvio, Amoroso, Nicola, Altomare, Cosimo Damiano, Bajorath, Jürgen, Nicolotti, Orazio (2023) CIRCE: Web-Based Platform for the Prediction of Cannabinoid Receptor Ligands Using Explainable Machine Learning. Journal of Chemical Information and Modeling, 63 (18) 5916-5926 doi:10.1021/acs.jcim.3c00914
In(2023, September) Journal of Chemical Information and Modeling Vol. 63 (18) American Chemical Society (ACS)

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